Upon first hearing the term ‘data scientist’, you may have an inkling that it refers to a role that utilizes data analysis and AI. Indeed, it does. However, it extends beyond that, requiring a diverse range of skills that has led it to be dubbed the ‘sexiest job of the 21st century’. Despite its allure, Japan faces a considerable gap between the demand for and supply of data scientists, with an estimated shortage of around 2.3 million individuals. The roots of this deficit can be traced back to several societal and individual challenges. Let’s delve into what these issues are and how they can be addressed.
Societal Challenges
1. STEM Education in Japan
The 2018 OECD’s PISA results showed that Japanese students scored an average of 544 in natural sciences, higher than the OECD average. However, they lagged in digital literacy, scoring only 487, indicating a lesser interest in data science compared to traditional scientific fields.
2. Digital Economy Development
The 2020 OECD’s Digital Economy Development Index (DEI) ranked Japan 21st out of 34 countries. This index, evaluating factors like access to and usage of digital technologies, level of digital innovation, and the impact of digital technologies on the labor market, reveals the gap in demand and supply of data scientists in Japan.
3. Corporate Data Utilization
According to the Ministry of Economy, Trade and Industry’s 2019 survey, while around 60% of companies reported collecting, analyzing, and utilizing data, only about 20% were capable of doing so in-house. This points to a clear shortage of talent capable of leveraging data within organizations.
Individual Challenges
1. Need for a Broad and Advanced Skillset
Data science spans a wide array of fields, requiring mathematics, statistics, computer science, and specific industry knowledge. Furthermore, the ability to integrate these skills and derive insights to solve complex problems is essential. A 2017 Kaggle survey found that about 50% of data scientists hold an advanced degree, underscoring the depth of expertise needed to succeed in this field.
2. Continual Learning Requirement
The fast-paced evolution of data science, with new tools and algorithms constantly being developed, necessitates continuous learning. This can be a significant burden, especially for those already engaged in full-time employment. According to a 2019 survey by Towards Data Science, data scientists spend about 40% of their working hours acquiring new knowledge.
3. Lack of Practical Experience
Real-world experience is crucial to becoming a data scientist, but opportunities to gain such experience are limited. Handling actual data science projects and solving problems provides vital skills that cannot be obtained through learning alone. Yet, as per Kaggle’s survey, around 45% of individuals lack practical experience as data scientists.
Overcoming the Challenges
To bridge the data scientist gap in Japan, concerted efforts from society and individuals are needed. We must reform education, improve corporate data utilization environments, and each of us should strive for skill enhancement and continual learning. It’s not an easy path, but it leads to new possibilities that can drive the digital age.
In the face of adversity, remember that you are the future data scientist. Every obstacle is just a step. It’s you who can bounce back and shape the new world! Armed with strategy and action, each challenge becomes an opportunity for continued growth.
With this mindset, we can move forward to tackle the challenges at hand and shape the future of data science in Japan.
